Evidence map›Paper›PMID 35961696›Full record

ArticleAdvances in cancer research2022

Liver cancer risk-predictive molecular biomarkers specific to clinico-epidemiological contexts.

Naoto Kubota, Naoto Fujiwara, Yujin Hoshida

Open access · greenAbstract read
In one paragraph

Article in Advances in cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.8field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 2 countries.

Naoto KubotaLiver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States.
Naoto FujiwaraLiver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States; Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Yujin HoshidaLiver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States. Electronic address: yujin.hoshida@utsouthwestern.edu.
The University of Texas Southwestern Medical Center · US

Funding

Reverse-engineering precision liver cancer chemopreventionR01CA233794 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI HOSHIDA, YUJIN · 2019 to 2023
$3.5M
Glycopathology of HCC: identification of the source cells of serum fucosylationU01CA226052 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI DRAKE, RICHARD R., HOSHIDA, YUJIN · 2019 to 2023
$2.8M
Molecular Prognostic Indicators in Liver Cirrhosis and CancerR01DK099558 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI HOSHIDA, YUJIN · 2013 to 2016
$2.6M
European Research Council 101021417European Research Council 671231NCI NIH HHS R01 CA233794NCI NIH HHS U01 CA226052NIDDK NIH HHS R01 DK099558
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) risk prediction is increasingly important because of the low annual HCC incidence in patients with the rapidly emerging non-alcoholic fatty liver disease or cured HCV infection. To date, numerous clinical HCC risk biomarkers and scores have been reported in literature. However, heterogeneity in clinico-epidemiological context, e.g., liver disease etiology, patient race/ethnicity, regional environmental exposure, and lifestyle-related factors, obscure their real clinical utility and applicability. Proper characterization of these factors will help refine HCC risk prediction according to certain clinical context/scenarios and contribute to improved early HCC detection. Molecular factors underlying the clinical heterogeneity encompass various features in host genetics, hepatic and systemic molecular dysregulations, and cross-organ interactions, which may serve as clinical-context-specific biomarkers and/or therapeutic targets. Toward the goal to enable individual-risk-based HCC screening by incorporating the HCC risk biomarkers/scores, their assessment in patient with well-defined clinical context/scenario is critical to gauge their real value and to maximize benefit of the tailored patient management for substantial improvement of the poor HCC prognosis.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsNon-alcoholic Fatty Liver DiseaseBiomarkersHumansLiver CirrhosisRisk FactorsBiomarkersCancer screeningCirrhosisClinical risk scoreHepatocellular carcinomaMolecular risk scorePrecision medicineRisk prediction

Identifiers

PMID35961696
PMCPMC7616039
OpenAlexW4214855382

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.